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Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification 被引量:1
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作者 Romany F.Mansour Eatedal Alabdulkreem 《Computer Systems Science & Engineering》 SCIE EI 2023年第2期1161-1169,共9页
The analysis of remote sensing image areas is needed for climate detec-tion and management,especially for monitoringflood disasters in critical environ-ments and applications.Satellites are mostly used to detect disast... The analysis of remote sensing image areas is needed for climate detec-tion and management,especially for monitoringflood disasters in critical environ-ments and applications.Satellites are mostly used to detect disasters on Earth,and they have advantages in capturing Earth images.Using the control technique,Earth images can be used to obtain detailed terrain information.Since the acquisi-tion of satellite and aerial imagery,this system has been able to detectfloods,and with increasing convenience,flood detection has become more desirable in the last few years.In this paper,a Big Data Set-based Progressive Image Classification Algorithm(PICA)system is introduced to implement an image processing tech-nique,detect disasters,and determine results with the help of the PICA,which allows disaster analysis to be extracted more effectively.The PICA is essential to overcoming strong shadows,for proper access to disaster characteristics to false positives by operators,and to false predictions that affect the impact of the disas-ter.The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches.Two types of proposed PICA systems detect disasters faster and more accurately(95.6%). 展开更多
关键词 CLUSTERING SEGMENTATION progressive image classification algorithm satellite image disaster detection
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PRECESION: progressive recovery and restoration planning of interdependent services in enterprise data centers 被引量:2
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作者 Ibrahim El-Shekeil Amitangshu Pal Krishna Kant 《Digital Communications and Networks》 SCIE 2018年第1期39-47,共9页
The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterpri... The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1]. 展开更多
关键词 progressive restoration planning Enterprise data center Genetic algorithm Integer linear program Multi-layer networks
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Short-term Transmission Maintenance Scheduling Considering Network Topology Optimization 被引量:4
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作者 Weixin Zhang Bo Hu +6 位作者 Kaigui Xie Changzheng Shao Tao Niu Jiahao Yan Lvbin Peng Maosen Cao Yue Sun 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2022年第4期883-893,共11页
With the increasing penetration of renewable energy sources,transmission maintenance scheduling(TMS)will have a larger impact on the accommodation of wind power.Meanwhile,the more flexible transmission network topolog... With the increasing penetration of renewable energy sources,transmission maintenance scheduling(TMS)will have a larger impact on the accommodation of wind power.Meanwhile,the more flexible transmission network topology owing to the network topology optimization(NTO)technique can ensure the secure and economic operation of power systems.This paper proposes a TMS model considering NTO to decrease the wind curtailment without adding control devices.The problem is formulated as a two-stage stochastic mixed-integer programming model.The first stage arranges the maintenance periods of transmission lines.The second stage optimizes the transmission network topology to minimize the maintenance cost and system operation in different wind speed scenarios.The proposed model cannot be solved efficiently with off-theshelf solvers due to the binary variables in both stages.Therefore,the progressive hedging algorithm is applied.The results on the modified IEEE RTS-79 system show that the proposed method can reduce the negative impact of transmission maintenance on wind accommodation by 65.49%,which proves its effectiveness. 展开更多
关键词 Mixed-integer linear programming network topology optimization progressive hedging algorithm stochastic optimization transmission maintenance scheduling wind curtailment
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